Technical Field
The present invention relates to an information processing apparatus, an image capturing apparatus, a control system, an information processing method, and a storage of program of method applicable to a moveable apparatus.
Background Art
Driver assistance systems for vehicles include a stereo camera to capture images of objects ahead of the vehicles. For example, the driver assistance system can capture images of objects ahead of the vehicle using the stereo camera disposed at a front side of the vehicle, process the captured images to find a range to the objects such as vehicles, persons, and others. If the vehicle is to be collide other objects, an alarm or warning can be informed to a driver, and a braking system can be activated to decrease the speed of the vehicle or to stop the vehicle.
The range finding by the stereo camera is performed by detecting a difference (i.e., disparity) of image-focused positions of two captured images when the same object is captured from two viewpoints, in which the difference (i.e., disparity) of image-focused positions of the two captured images changes depending on the distance to the object.
The stereo camera capture one image as a reference image, and another image as a comparing image. Then, the disparity of one pixel in the reference image can be calculated by performing a matching process with candidate pixels in a search range set in the comparing image. After completing the matching process to the entire search range, the disparity of the most matched point can be set as the most probable disparity.
The matching process can employ a block matching method, in which a correlation evaluation value (i.e., matching evaluation value) of a small area between the reference image and the comparing image is calculated, and a shift amount (deviation) between the reference image and the comparing image having the most probable correlation evaluation value is calculated as the disparity.
The correlation evaluation value can be Sum of Absolute Difference (SAD), which is a sum of absolute difference of pixel values of two small areas, Sum of Squared Difference (SSD), which is a sum of squared difference, and Zero-mean-Sum of Squared Difference (ZSSD), which is obtained by subtracting an average value of each block from SSD value. Since these evaluation values become smaller as the correlation level becomes higher (i.e., matching level becomes higher), these evaluation values can be used to indicate the dissimilarity level.
FIG. 16 is an example of a profile obtained by performing a matching process. In a case of FIG. 16, the horizontal axis represents a search range, which means the shift amount (deviation) of pixel positions in the comparing image relative to a pixel position in the reference image, and the vertical axis represents the correlation evaluation value indicating the dissimilarity level. In a case of FIG. 16, the dissimilarity level becomes the minimum at the seventh pixel in the search range indicated by a circle, and thereby “seven (7)” becomes the most probable disparity expressed by a whole number. A negative value in the search range on the horizontal axis is used to obtain a sub-pixel disparity.
However, when an image of an object having a repetitive pattern such as building window, tile wall, and fence is captured to calculate the disparity of the object, the matching portion can be detected at two or more portions such as six portions as illustrated in FIG. 17, with which the most probable disparity may not be output correctly but a wrong disparity may be output erroneously.
If the wrong disparity is output erroneously, even if the object having the repetitive pattern actually exists at a far point, data indicating that the object exists at a near point is output erroneously. If the automatic braking system of the vehicle is activated based on the erroneous data, the automatic braking system activates the braking of the vehicle at a point where the braking is not required actually, which is referred to “wrong braking.”
In view of this issue, a vehicle-mounted object detection apparatus including a stereo camera is employed, in which stereo images captured by the stereo camera are processed based on a similarity level of each small area in one-side image and another side image of the stereo images. Specifically, when a corresponding position of the two images is computed, it is checked whether a value close to the highest similarity level is detected at a plurality of portions. If the value close to the highest similarity level is detected at the plurality of portions, it is determined that the distance obtained from the small area is a wrong distance caused by the repetitive pattern, and the determined distance is not used for the object detection and measurement. With this configuration, a wrong detection of the object caused by a wrong matching of stereo images caused by the repetitive pattern such as a stripe pattern of crosswalk can be prevented.
However, as to the above described vehicle-mounted object detection apparatus, the determination whether data can be used for detecting the object and measuring the distance to the object is performed after completing the matching process for the entire search range. Therefore, time to obtain the determination result becomes long.